A Combinatorial Approach for Optimizing Transportation System: Multi-Objective Decision-Making Framework

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F24%3A00378662" target="_blank" >RIV/68407700:21260/24:00378662 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.14311/NNW.2024.34.008" target="_blank" >https://doi.org/10.14311/NNW.2024.34.008</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14311/NNW.2024.34.008" target="_blank" >10.14311/NNW.2024.34.008</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Combinatorial Approach for Optimizing Transportation System: Multi-Objective Decision-Making Framework

Popis výsledku v původním jazyce

This study presents a comprehensive multi-objective transportation model aimed at optimizing complex vehicle routing problems, which are nondeterministic polynomial time NP-hard due to spatial, temporal, and capacity constraints. In this study, the multi-objective transportation model integrates decisionmaker preferences with hybrid optimization techniques, including the approximatecombinatorial method, ant colony optimization and evolutionary algorithms. it seeks to minimize transportation costs, time, and emissions while accounting for real-world constraints such as fleet composition, customer demand, and servicelevel agreements. The techniques like multi-criteria decision-making methods are employed to refine the solution set, balancing objectives like cost, time, environmental impact, and service level. The novel optimization model is applied to a fuel distribution case study involving 18 customers and a heterogeneous fleet, where it optimizes vehicle routes to meet delivery requirements efficiently. The multiobjective transportation framework generates multiple feasible solutions, which are further narrowed down using decision-making frameworks to ensure alignment with organizational goals and decision-maker preferences. The integration of quantitative optimization techniques with qualitative decision-making processes makes this model robust and scalable, offering a practical tool for enhancing operational efficiency in transportation systems. This approach effectively addresses real-world logistics challenges, demonstrating significant improvements in route efficiency, cost savings, and environmental sustainability.

Název v anglickém jazyce

A Combinatorial Approach for Optimizing Transportation System: Multi-Objective Decision-Making Framework

Popis výsledku anglicky

This study presents a comprehensive multi-objective transportation model aimed at optimizing complex vehicle routing problems, which are nondeterministic polynomial time NP-hard due to spatial, temporal, and capacity constraints. In this study, the multi-objective transportation model integrates decisionmaker preferences with hybrid optimization techniques, including the approximatecombinatorial method, ant colony optimization and evolutionary algorithms. it seeks to minimize transportation costs, time, and emissions while accounting for real-world constraints such as fleet composition, customer demand, and servicelevel agreements. The techniques like multi-criteria decision-making methods are employed to refine the solution set, balancing objectives like cost, time, environmental impact, and service level. The novel optimization model is applied to a fuel distribution case study involving 18 customers and a heterogeneous fleet, where it optimizes vehicle routes to meet delivery requirements efficiently. The multiobjective transportation framework generates multiple feasible solutions, which are further narrowed down using decision-making frameworks to ensure alignment with organizational goals and decision-maker preferences. The integration of quantitative optimization techniques with qualitative decision-making processes makes this model robust and scalable, offering a practical tool for enhancing operational efficiency in transportation systems. This approach effectively addresses real-world logistics challenges, demonstrating significant improvements in route efficiency, cost savings, and environmental sustainability.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20104 - Transport engineering

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Neural Network World

ISSN

1210-0552

e-ISSN

2336-4335

Svazek periodika

34

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

34

Strana od-do

135-168

Kód UT WoS článku

001414977900001

EID výsledku v databázi Scopus

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